Unified Metadata Graph for Accessing Siloed Data Without Replication
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Solution Overview
Problem
Existing systems require significant computational resources and cause data integrity issues when accessing siloed data across disparate locations due to the need for creating new data silos and reconfiguring computing systems, leading to inefficiencies and potential data corruption.
Innovation Solution
A unified metadata graph system that uses natural language processing to interpret user queries, determines relevant data silos through a metadata graph, and provides a visual interface for accessing data without creating new silos, thereby reducing computational resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If new data silos are created to access siloed data, then data accessibility is improved, but computational resource usage increases and data integrity risks worsen
Solution Approach 1:
The patent introduces a metadata graph as an intermediary layer between users and data silos. The metadata graph stores metadata about data locations, types, and relationships, allowing the system to query and access data across multiple silos without creating new silos or copying data. This mediator enables efficient data discovery and access while avoiding the computational overhead of data duplication.
Solution Approach 2:
Instead of copying data to new silos, the patent creates a virtual copy of data locations through the metadata graph. The metadata graph stores references to actual data locations across existing silos, enabling multiple users and systems to access the same data without physical duplication. This approach maintains data integrity while improving accessibility.
2Adaptability or versatility
If data is replicated across multiple silos for different computing systems, then data availability is improved, but data integrity and consistency deteriorate
Solution Approach 1:
The metadata graph serves as a mediator that tracks data locations and relationships without replicating the data itself. By storing metadata about where data resides and how it relates to other data, the system maintains a single source of truth while enabling data to be accessed from multiple locations simultaneously, thus preserving integrity while improving availability.
3Adaptability or versatility
If computing systems are reconfigured to access siloed data, then data integration is improved, but system complexity and time required increase
Solution Approach 1:
The metadata graph is pre-built and maintained with information about data locations, types, and relationships across all silos. This preliminary organization of metadata allows the system to quickly answer data access queries without requiring real-time reconfiguration of computing systems. The metadata graph is updated as data moves between silos, maintaining current information without system reconfiguration.
Solution Approach 2:
The metadata graph acts as an intermediary that abstracts the complexity of data distribution across silos. Instead of requiring computing systems to understand and reconfigure connections to multiple silos, the metadata graph provides a simplified interface that translates high-level data access requests into specific silo queries, reducing reconfiguration time and system complexity.
Data Source
AI summary
Systems and methods for reducing usage of computational resources when accessing siloed data across disparate locations via a unified metadata graph are disclosed. The system receives a user-specified query indicating a request to access a set of data objects. The system then performs natural language processing on the user-specified query to determine a set of phrases corresponding to the user-specified query. The system then accesses a metadata graph to determine a node corresponding to the set of phrases. Using a location identifier corresponding to the determined node, the system determines a data silo storing at least one data object of the set of data objects. The system then generates for display, on a graphical user interface, a visual representation of the at least one data object.